User operation of video imaging devices, and in particular hand-held recording devices, can produce blurred or displaced image data due to small movements of the operator while supporting the imaging device. Blurred or distorted image data, however, is not preferred. Accordingly, conventional methods and devices have been employed for stabilization of image data captured by video imaging devices. For example, one conventional method includes employing one or more motion sensors to detect motion of the imaging device for correction of image data. These methods require motion sensors and can still result in digital distortions as the motion sensing arrangements typically employed usually do not detect rotational motion. Difficulties with image stabilization may additionally increase using zoom features of the imaging device.
The conventional methods and devices, however, do not account for real-time, or near real-time, digital video stabilization for image data captured by CMOS sensors, in particular rolling shutter sensors. Previous attempts have been directed at performing off-line post-processing to compensate for translational transformation. These methods, however, do not account for outliers introduced by local object motion or correct for rolling shutter imaging artifacts. Another approach involves off-line processing which usually differs from on-line processing by requiring higher power consumption, higher bandwidth, higher processing delay and higher algorithmic complexity.
Thus, there is a need in the art for systems and methods to address one or more drawbacks of devices employing CMOS sensors.